Improved Material Decomposition With a Two-Step Regularization for Spectral CT

IEEE Access

Hengyong Yu¹  Weiwen Wu²  Vince Varut Vardhanabhuti²  Weifei Wu³  Peijun Chen³ 

[1] Department of Diagnostic Radiology, The University of Hong Kong, Hong Kong;Department of Orthopedics, The People&x2019;s Hospital of China Three Gorges University, Yichang, China;

关键词: Spectral computed tomography;    two-step regularization;    image reconstruction;    material decomposition;   

DOI  :  10.1109/ACCESS.2019.2950427

来源: DOAJ

【 摘 要 】

One of the advantages of spectral computed tomography (CT) is it can achieve accurate material components using the material decomposition methods. The image-based material decomposition is a common method to obtain specific material components, and it can be divided into two steps: image reconstruction and post material decomposition. To obtain accurate material maps, the image reconstruction method mainly focuses on improving image quality by incorporating regularization priors. Very recently, the regularization priors are introduced into the post material decomposition procedure in the iterative image-based methods. Since the regularization priors can be incorporated into image reconstruction and post image-domain material decomposition, the performance of regularization by combining these two cases is still an open problem. To realize this goal, the material accuracy from those steps are first analyzed and compared. Then, to further improve the accuracy of decomposition materials, a two-step regularization based method is developed by incorporating priors into image reconstruction and post material decomposition. Both numerical simulation and preclinical mouse experiments are performed to demonstrate the advantages of the two-step regularization based method in improving material accuracy.

【 授权许可】

Unknown